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A Visual Guide to Stata Graphics

A Visual Guide to Stata Graphics

Whether you are new to Stata graphics or a seasoned veteran this book will teach you how to use Stata to make publication-quality graphs that will stand out and enhance your statistical results. With over 1 200 illustrated examples and quick-reference tabs this book quickly guides you to the information you need for creating and customizing high-quality graphs for any type of statistical data. Each graph is displayed in full color with simple and clear instructions that illustrate how to create and customize graphs using Stata commands. Whether you use this book as a learning tool or a quick reference you will have the power of Stata graphics at your fingertips. | A Visual Guide to Stata Graphics

GBP 74.99
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Multilevel and Longitudinal Modeling Using Stata Volume II Categorical Responses Counts and Survival

Multilevel and Longitudinal Modeling Using Stata Volume II Categorical Responses Counts and Survival

Multilevel and Longitudinal Modeling Using Stata Fourth Edition is a complete resource for learning to model data in which observations are grouped. With comprehensive coverage researchers who need to apply multilevel models will find this book to be the perfect companion. It is also the ideal text for courses in multilevel modeling because it provides examples from a variety of disciplines as well as end-of-chapter exercises that allow students to practice newly learned material. The book comprises two volumes. Volume II focuses on generalized linear models for binary ordinal count and other types of outcomes. | Multilevel and Longitudinal Modeling Using Stata Volume II Categorical Responses Counts and Survival

GBP 69.99
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Microeconometrics Using Stata Second Edition Volumes I and II

Microeconometrics Using Stata Second Edition Volumes I and II

Microeconometrics Using Stata Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods. Like previous editions this text covers all the classic microeconometric techniques ranging from linear models to instrumental-variables regression to panel-data estimation to nonlinear models such as probit tobit Poisson and choice models. Each of these discussions has been updated to show the most modern implementation in Stata and many include additional explanation of the underlying methods. In addition the authors introduce readers to performing simulations in Stata and then use simulations to illustrate methods in other parts of the book. They even teach you how to code your own estimators in Stata. The second edition is greatly expanded—the new material is so extensive that the text now comprises two volumes. In addition to the classics the book now teaches recently developed econometric methods and the methods newly added to Stata. Specifically the book includes entirely new chapters on duration models randomized control trials and exogenous treatment effects endogenous treatment effects models for endogeneity and heterogeneity including finite mixture models structural equation models and nonlinear mixed-effects models spatial autoregressive models semiparametric regression lasso for prediction and inference Bayesian analysis Anyone interested in learning classic and modern econometric methods will find this the perfect companion. And those who apply these methods to their own data will return to this reference over and over as they need to implement the various techniques described in this book. | Microeconometrics Using Stata Second Edition Volumes I and II

GBP 150.00
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Microeconometrics Using Stata Second Edition Volume I: Cross-Sectional and Panel Regression Models

Microeconometrics Using Stata Second Edition Volume I: Cross-Sectional and Panel Regression Models

Microeconometrics Using Stata Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods. Like previous editions this text covers all the classic microeconometric techniques ranging from linear models to instrumental-variables regression to panel-data estimation to nonlinear models such as probit tobit Poisson and choice models. Each of these discussions has been updated to show the most modern implementation in Stata and many include additional explanation of the underlying methods. In addition the authors introduce readers to performing simulations in Stata and then use simulations to illustrate methods in other parts of the book. They even teach you how to code your own estimators in Stata. The second edition is greatly expanded—the new material is so extensive that the text now comprises two volumes. In addition to the classics the book now teaches recently developed econometric methods and the methods newly added to Stata. Specifically the book includes entirely new chapters on duration models randomized control trials and exogenous treatment effects endogenous treatment effects models for endogeneity and heterogeneity including finite mixture models structural equation models and nonlinear mixed-effects models spatial autoregressive models semiparametric regression lasso for prediction and inference Bayesian analysis Anyone interested in learning classic and modern econometric methods will find this the perfect companion. And those who apply these methods to their own data will return to this reference over and over as they need to implement the various techniques described in this book. | Microeconometrics Using Stata Second Edition Volume I: Cross-Sectional and Panel Regression Models

GBP 89.99
1

Microeconometrics Using Stata Second Edition Volume II: Nonlinear Models and Casual Inference Methods

Microeconometrics Using Stata Second Edition Volume II: Nonlinear Models and Casual Inference Methods

Microeconometrics Using Stata Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods. Like previous editions this text covers all the classic microeconometric techniques ranging from linear models to instrumental-variables regression to panel-data estimation to nonlinear models such as probit tobit Poisson and choice models. Each of these discussions has been updated to show the most modern implementation in Stata and many include additional explanation of the underlying methods. In addition the authors introduce readers to performing simulations in Stata and then use simulations to illustrate methods in other parts of the book. They even teach you how to code your own estimators in Stata. The second edition is greatly expanded—the new material is so extensive that the text now comprises two volumes. In addition to the classics the book now teaches recently developed econometric methods and the methods newly added to Stata. Specifically the book includes entirely new chapters on duration models randomized control trials and exogenous treatment effects endogenous treatment effects models for endogeneity and heterogeneity including finite mixture models structural equation models and nonlinear mixed-effects models spatial autoregressive models semiparametric regression lasso for prediction and inference Bayesian analysis Anyone interested in learning classic and modern econometric methods will find this the perfect companion. And those who apply these methods to their own data will return to this reference over and over as they need to implement the various techniques described in this book. | Microeconometrics Using Stata Second Edition Volume II: Nonlinear Models and Casual Inference Methods

GBP 89.99
1

Psychological Statistics and Psychometrics Using Stata

Psychological Statistics and Psychometrics Using Stata

Psychological Statistics and Psychometrics Using Stata is a complete and concise resource for students and researchers in the behavioral sciences. The author’s primary goal in this book is to help readers become competent users of statistics. To that end he first introduces basic statistical methods such as regression t tests and ANOVA. He focuses on explaining the models how they can be used with different types of variables and how to interpret the results. After building this foundation the author covers more advanced statistical techniques including power-and-sample size calculations multilevel modeling and structural equation modeling. This book also discusses measurement concepts that are crucial in psychometrics. For instance the author explores how reliability and validity can be understood and evaluated using exploratory and confirmatory factor analysis. The author includes dozens of worked examples using real data to illustrate the theory and concepts.

GBP 55.99
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A Gentle Introduction to Stata Revised Sixth Edition

A Gentle Introduction to Stata Revised Sixth Edition

Alan C. Acock's A Gentle Introduction to Stata Revised Sixth Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text new users will be able to not only use Stata well but also learn new aspects of Stata. Acock assumes that the user is not familiar with any statistical software. This assumption of a blank slate is central to the structure and contents of the book. Acock starts with the basics; for example the part of the book that deals with data management begins with a careful and detailed example of turning survey data on paper into a Stata-ready dataset. When explaining how to go about basic exploratory statistical procedures Acock includes notes that will help the reader develop good work habits. This mixture of explaining good Stata habits and explaining good statistical habits continues throughout the book. Acock is quite careful to teach the reader all aspects of using Stata. He covers data management good work habits (including the use of basic do-files) basic exploratory statistics (including graphical displays) and analyses using the standard array of basic statistical tools (correlation linear and logistic regression and parametric and nonparametric tests of location and dispersion). He also successfully introduces some more advanced topics such as multiple imputation and multilevel modeling in a very approachable manner. Acock teaches Stata commands by using the menus and dialog boxes while still stressing the value of Stata commands and do-files. In this way he ensures that all types of users can build good work habits. Each chapter has exercises that the motivated reader can use to reinforce the material. The tone of the book is friendly and conversational without ever being glib or condescending. Important asides and notes about terminology are set off in boxes which makes the text easy to read without any convoluted twists or forward referencing. Rather than splitting topics by their Stata implementation Acock arranges the topics as they would appear in a basic statistics textbook; graphics and postestimation are woven into the material naturally. Real datasets such as the General Social Surveys from 2002 2006 and 2016 are used throughout the book. The focus of the book is especially helpful for those in the behavioral and social sciences because the presentation of basic statistical modeling is supplemented with discussions of effect sizes and standardized coefficients. Various selection criteria such as semipartial correlations are discussed for model selection. Acock also covers a variety of commands available for evaluating reliability and validity of measurements. The revised sixth edition is fully up to date for Stata 17 including updated discussion and images of Stata's interface and modern command syntax. In addition examples include new features such as the table command and collect suite for creating and exporting customized tables as well as the option for creating graphs with transparency.

GBP 59.99
1

Interpreting and Visualizing Regression Models Using Stata

Interpreting and Visualizing Regression Models Using Stata

Interpreting and Visualizing Regression Models Using Stata Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures the book illustrates linear models with continuous predictors (modeled linearly using polynomials and piecewise) interactions of continuous predictors categorical predictors interactions of categorical predictors and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models models where time is a continuous predictor models with time as a categorical predictor nonlinear models (such as logistic or ordinal logistic regression) and models involving complex survey data. The examples illustrate the use of the margins marginsplot contrast and pwcompare commands. This new edition reflects new and enhanced features added to Stata most importantly the ability to label statistical output using value labels associated with factor variables. As a result output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally this second edition illustrates other new features such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata this book is for you.

GBP 59.99
1

Maximum Likelihood Estimation with Stata Fifth Edition

Maximum Likelihood Estimation with Stata Fifth Edition

Maximum Likelihood Estimation with Stata Fifth Edition is the essential reference and guide for researchers in all disciplines who wish to write maximum likelihood (ML) estimators in Stata. Beyond providing comprehensive coverage of Stata’s commands for writing ML estimators the book presents an overview of the underpinnings of maximum likelihood and how to think about ML estimation. The fifth edition includes a new second chapter that demonstrates the easy-to-use mlexp command. This command allows you to directly specify a likelihood function and perform estimation without any programming. The core of the book focuses on Stata's ml command. It shows you how to take full advantage of ml’s noteworthy features: Linear constraints Four optimization algorithms (Newton–Raphson DFP BFGS and BHHH) Observed information matrix (OIM) variance estimator Outer product of gradients (OPG) variance estimator Huber/White/sandwich robust variance estimator Cluster–robust variance estimator Complete and automatic support for survey data analysis Direct support of evaluator functions written in Mata When appropriate options are used many of these features are provided automatically by ml and require no special programming or intervention by the researcher writing the estimator. In later chapters you will learn how to take advantage of Mata Stata's matrix programming language. For ease of programming and potential speed improvements you can write your likelihood-evaluator program in Mata and continue to use ml to control the maximization process. A new chapter in the fifth edition shows how you can use the moptimize() suite of Mata functions if you want to implement your maximum likelihood estimator entirely within Mata. In the final chapter the authors illustrate the major steps required to get from log-likelihood function to fully operational estimation command. This is done using several different models: logit and probit linear regression Weibull regression the Cox proportional hazards model random-effects regression and seemingly unrelated regression. This edition adds a new example of a bivariate Poisson model a model that is not available otherwise in Stata. The authors provide extensive advice for developing your own estimation commands. With a little care and the help of this book users will be able to write their own estimation commands-commands that look and behave just like the official estimation commands in Stata. Whether you want to fit a special ML estimator for your own research or wish to write a general-purpose ML estimator for others to use you need this book.

GBP 59.99
1

Multilevel and Longitudinal Modeling Using Stata Volumes I and II

Multilevel and Longitudinal Modeling Using Stata Volumes I and II

Multilevel and Longitudinal Modeling Using Stata Fourth Edition is a complete resource for learning to model data in which observations are grouped—whether those groups are formed by a nesting structure such as children nested in classrooms or formed by repeated observations on the same individuals. This text introduces random-effects models fixed-effects models mixed-effects models marginal models dynamic models and growth-curve models all of which account for the grouped nature of these types of data. As Rabe-Hesketh and Skrondal introduce each model they explain when the model is useful its assumptions how to fit and evaluate the model using Stata and how to interpret the results. With this comprehensive coverage researchers who need to apply multilevel models will find this book to be the perfect companion. It is also the ideal text for courses in multilevel modeling because it provides examples from a variety of disciplines as well as end-of-chapter exercises that allow students to practice newly learned material. The book comprises two volumes. Volume I focuses on linear models for continuous outcomes while volume II focuses on generalized linear models for binary ordinal count and other types of outcomes. | Multilevel and Longitudinal Modeling Using Stata Volumes I and II

GBP 120.00
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Health Econometrics Using Stata

Health Econometrics Using Stata

Health Econometrics Using Stata by Partha Deb Edward C. Norton and Willard G. Manning provides an excellent overview of the methods used to analyze data on healthcare expenditure and use. Aimed at researchers graduate students and practitioners this book introduces readers to widely used methods shows them how to perform these methods in Stata and illustrates how to interpret the results. Each method is discussed in the context of an example using an extract from the Medical Expenditure Panel Survey. After the overview chapters the book provides excellent introductions to a series of topics aimed specifically at those analyzing healthcare expenditure and use data. The basic topics of linear regression the generalized linear model and log and Box-Cox models are covered with a tight focus on the problems presented by these data. Using this foundation the authors cover the more advanced topics of models for continuous outcome with mass points count models and models for heterogeneous effects. Finally they discuss endogeneity and how to address inference questions using data from complex surveys. The authors use their formidable experience to guide readers toward useful methods and away from less recommended ones. Their discussion of health econometric myths and the chapter presenting a framework for approaching health econometric estimation problems are especially useful for this aspect.

GBP 55.99
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An Introduction to Stata for Health Researchers

An Introduction to Stata for Health Researchers

An Introduction to Stata for Health Researchers Fifth Edition updates this classic book that has become a standard reference for health researchers. As with previous editions readers will learn to work effectively in Stata to perform data management compute descriptive statistics create meaningful graphs fit regression models and perform survival analysis. The fifth edition adds examples of performing power precision and sample-size analysis; working with Unicode characters; managing data with ICD-9 and ICD-10 codes; and creating customized tables. With many worked examples and downloadable datasets this text is the ideal resource for hands-on learning whether for students in a statistics course or for researchers in fields such as epidemiology biostatistics and public health who are learning to use Stata's tools for health research.

GBP 59.99
1

Data Management Using Stata A Practical Handbook

Data Management Using Stata A Practical Handbook

This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats the ability to write highly customized Excel files the ability to have multiple Stata datasets open at once and the ability to store and manipulate string variables stored as Unicode. Further this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition the chapters are organized by data management areas: reading and writing datasets cleaning data labeling datasets creating variables combining datasets processing observations across subgroups changing the shape of datasets and programming for data management. Within each chapter each section is a self-contained lesson illustrating a particular data management task (for instance creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the “nuts and bolts” examples author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management while experienced users will find this information to be handy and time saving—there is a good chance that even the experienced user will learn some new tricks. | Data Management Using Stata A Practical Handbook

GBP 61.99
1

A Course in Item Response Theory and Modeling with Stata

A Course in Item Response Theory and Modeling with Stata

Over the past several decades item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral educational social business marketing clinical and health sciences. In this book Raykov and Marcoulides begin with a nontraditional approach to IRT and IRM that is based on their connections to classical test theory (nonlinear) factor analysis generalized linear modeling and logistic regression. Application-oriented discussions follow next. These cover the one- two- and three-parameter logistic models polytomous item response models (with nominal or ordinal items) item and test information functions instrument construction and development hybrid models differential item functioning and an introduction to multidimensional IRT and IRM. The pertinent analytic and modeling capabilities of Stata are thoroughly discussed highlighted and illustrated on empirical examples from behavioral and social research. | A Course in Item Response Theory and Modeling with Stata

GBP 55.99
1